Our Industrial Digital Platform team is looking for a Data Engineer to build and scale the data backbone that powers decision-making across engineering, operations, and leadership.

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We are developing a modern data platform focused on transforming industrial and operational data into a reliable, high-quality asset. This role sits at the intersection of industrial systems and cloud data technologies, with a strong emphasis on data quality, governance, and scalability.

This is a hands‑on role for someone who takes ownership, cares deeply about data integrity, and is comfortable working across the full data stack.

Conditions

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- Permanent contract

- Hybrid model: 1 day of remote work per week

- Working hours: 9:30 a.m. to 6:30 p.m. (Fridays until 2:30 p.m.)

Mission of the role

Design, build, and maintain a robust, scalable, and validation‑first data infrastructure that ensures high‑quality, reliable data across the industrial digital platform.

You will act as a key contributor to data architecture and governance, ensuring that data is accurate, accessible, and trusted across all business functions.

Key responsibilities
Data Quality & Governance

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- Define and enforce validation standards across all data systems

- Ensure data accuracy, consistency, and integrity from ingestion to consumption

- Design and maintain data contracts, lineage tracking, and cataloguing practices

- Design, build, and maintain scalable data pipelines with validation embedded at every stage

ETL/ELT Development

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- Build and evolve ETL/ELT processes with automated quality checks

- Ensure issues are detected and resolved before reaching downstream users

Cross‑functional collaboration

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- Translate complex requirements from engineers, analysts,



and scientists into robust solutions

- Work closely with multiple teams to deliver production‑grade data systems

- Optimise database performance and storage architecture

- Ensure continuous reliability and efficiency of data systems

- Monitor pipeline health and proactively detect issues

- Diagnose failures quickly and ensure continuous data availability

- Stay up to date with data engineering trends and tools

- Introduce improvements that add real value to the platform

Profile

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- 6+ years of experience in data engineering, ideally in industrial or operational environments

- Strong SQL skills and hands‑on ETL/ELT experience with a focus on data quality

- Proficiency in Python, Java, or Scala

- Solid understanding of data modelling, data warehousing, and big data technologies (Spark, Hadoop)

- Proven experience with Azure and Databricks

- Experience in data governance (cataloguing, lineage, metadata, access control)

- Familiarity with data quality tools (Great Expectations, xqbhyrx dbt tests, Soda)

- Degree in Computer Science, Engineering, or a related field

- Strong problem‑solving skills and attention to detail

- Excellent communication skills across technical and non‑technical teams

Nice to Have

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- Experience building and optimising data lakes and warehouses in Azure

- Real‑time and streaming data processing (Event Hubs, Stream Analytics)

- Experience with data mesh or data fabric architectures

- Knowledge of regulatory frameworks (ISO, GDPR)

- Experience with containerisation and orchestration (Docker, Kubernetes, ADF)

Languages

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- Spanish – Highly valued

- Italian – Highly valued

What we offer

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- Strategic role with real impact on data‑driven decision making

- Dynamic and fast‑growing environment

- Opportunity to build and scale a modern industrial data platform

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📌 Data Analitics - Industrial Digital Platform (Madrid)
🏢 Verdalia Bioenergy
📍 Madrid